Up a level |
This graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
Use the mouse wheel or scroll gestures to zoom into the graph.
You can click on the nodes and links to highlight them and move the nodes by dragging them.
Hold down the "Ctrl" key or the "⌘" key while clicking on the nodes to open the list of this person's publications.
A word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Nguyen, A., Bougacha, O., Lekens, B., Lamouri, S., Pellerin, R., & Couvreur, C. (2022, November). On the use of logistics data to anticipate drugs shortages through data mining [Paper]. International Conference on ENTERprise Information Systems (CENTERIS 2022), Lisbon, Portugal. Published in Procedia Computer Science, 219. External link
Nguyen, A., Pellerin, R., Lamouri, S., & Lekens, B. (2022). Managing demand volatility of pharmaceutical products in times of disruption through news sentiment analysis. International Journal of Production Research, 61(9), 2829-2840. External link
Nguyen, A., Lamouri, S., Pellerin, R., Tamayo, S., & Lekens, B. (2021). Data analytics in pharmaceutical supply chains: state of the art, opportunities, and challenges. International Journal of Production Research, 60(22), 6888-6907. External link
Nguyen, A., Lamouri, S., & Pellerin, R. (2021, June). Managing demand volatility during unplanned events with sentiment analysis: a case study of the COVID-19 pandemic [Paper]. 17th IFAC Symposium on Information Control Problems in Manufacturing (INCOM 2021), Budapest, Hongrie. Published in IFAC-Papers Online, 54(1). External link
Nguyen, A., Usuga-Cadavid, J. P., Lamouri, S., Grabot, B., & Pellerin, R. (2020, October). Understanding Data-Related Concepts in Smart Manufacturing and Supply Chain Through Text Mining [Paper]. 10th International Workshop on Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future (SOHOMA 2020), Paris, France. External link